文献类型：期刊文献

中文题名：基于C5.0算法的森林资源变化检测方法研究——以山东省徂徕山林区为例

英文题名：Methodsological Study on the Detection of the Variations of Forest Resources Based on C5.0 Algorithm-A Case of Culai Forest in Shandong

作者：王志慧[1,2] 李世明[1] 张艺伟[2]

第一作者：王志慧

机构：[1]中国林业科学研究院资源信息研究所;[2]中国矿业大学(北京)

年份：2011

卷号：26

期号：5

起止页码：185-191

中文期刊名：西北林学院学报

外文期刊名：Journal of Northwest Forestry University

收录：CSTPCD;;北大核心:【北大核心2008】；CSCD:【CSCD_E2011_2012】；

基金：中央级公益性科研院所基本科研业务费专项课题(IFRIT200805);林业公益性行业科研专项(200804001)

语种：中文

中文关键词：变化检测;C5.0;决策树;邻近相关分析

外文关键词：change detection; C5.0; decision tree; neighborhood correlation analysis

分类号：S757.24

摘要：以山东省徂徕山林场为试验区,利用两时相的TM与ETM+遥感数据对该地区的针叶林、阔叶林等森林资源的变化进行研究。将基于C5.0算法的决策树分类方法应用于森林变化检测,并对3种检测方案进行试验比较:(1)以单一时相图像作为数据源并各自分类,分类后作比较提取变化信息;(2)以两时相图像的原始波段数据作为数据源训练规则,并生成变化检测图;(3)以两时相图像加上邻近相关分析图像作为数据源训练规则,生成变化检测图。试验结果表明,基于C5.0算法的决策树分类可以有效的进行森林变化检测,并且加入邻近相关分析图像后的变化检测精度达到最高。
With double-temporal TM and ETM＋ remote sensing data,the information of the variation of forest resources of Culai Mountain in Shandong Province,China was explored.Decision tree classification based on C5.0 algorithm to forest change detection was applied.Three different detection methods were compared：1） to classify single-temporal data by C5.0 respectively,and extract change information after comparing classification results;2） to create C5.0 train rules through double-temporal raw data,then generate change detection map;3） in addition to double-temporal remote sensing data,neighborhood correlation analysis images are also added as one of the data sources of C5.0,and generate change detection map of variation.The experimental result shows that decision tree classification based on C5.0 algorithm could detect variation information effectively,and after adding neighborhood correlation analysis images the classification accuracy of change detection was improved.